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<p>Base storage class for GPU memory with reference counting.  
 <a href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#details">More...</a></p>
<p><code>#include &lt;opencv2/core/cuda.hpp&gt;</code></p>
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Inheritance diagram for cv::cuda::GpuMat:</div>
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<tr class="memitem:"><td align="right" class="memItemLeft" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">Allocator</a></td></tr>
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Public Member Functions</h2></td></tr>
<tr class="memitem:a1ac7380bd407013cc35b150f6243c417"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1ac7380bd407013cc35b150f6243c417">GpuMat</a> (<a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a>=<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>())</td></tr>
<tr class="memdesc:a1ac7380bd407013cc35b150f6243c417"><td class="mdescLeft"> </td><td class="mdescRight">default constructor  <a href="#a1ac7380bd407013cc35b150f6243c417">More...</a><br/></td></tr>
<tr class="separator:a1ac7380bd407013cc35b150f6243c417"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ac93af62c4de452d69e61c0adef511429"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ac93af62c4de452d69e61c0adef511429">GpuMat</a> (int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7385022ca9114e5f5058dbb2f12467cb">rows</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a9265a32d8d29fe29804a0cb8f57213e9">cols</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>, <a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a>=<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>())</td></tr>
<tr class="memdesc:ac93af62c4de452d69e61c0adef511429"><td class="mdescLeft"> </td><td class="mdescRight">constructs <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> of the specified size and type  <a href="#ac93af62c4de452d69e61c0adef511429">More...</a><br/></td></tr>
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<tr class="memitem:a36a4b321e7b141f99d41c0b431f74c5e"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a36a4b321e7b141f99d41c0b431f74c5e">GpuMat</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab02f97698d8272f0d253f3029329ed10">size</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>, <a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a>=<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>())</td></tr>
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<tr class="memitem:a40333be65edc1191260d1f7252b0d72c"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a40333be65edc1191260d1f7252b0d72c">GpuMat</a> (int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7385022ca9114e5f5058dbb2f12467cb">rows</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a9265a32d8d29fe29804a0cb8f57213e9">cols</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>, <a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> s, <a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a>=<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>())</td></tr>
<tr class="memdesc:a40333be65edc1191260d1f7252b0d72c"><td class="mdescLeft"> </td><td class="mdescRight">constructs <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> and fills it with the specified value _s  <a href="#a40333be65edc1191260d1f7252b0d72c">More...</a><br/></td></tr>
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<tr class="memdesc:af1fd1025a62d333c9c970ca3761a23db"><td class="mdescLeft"> </td><td class="mdescRight">copy constructor  <a href="#af1fd1025a62d333c9c970ca3761a23db">More...</a><br/></td></tr>
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<tr class="memitem:ab7210166f4bd124855b520b3dde28fb1"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab7210166f4bd124855b520b3dde28fb1">GpuMat</a> (int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7385022ca9114e5f5058dbb2f12467cb">rows</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a9265a32d8d29fe29804a0cb8f57213e9">cols</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>, void *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a5139f9492f9079c7b9e414d50da332a3">data</a>, size_t <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af46427ea4c9b3fe7687e3afa84baede3">step</a>=<a class="el" href="../../d3/d63/classcv_1_1Mat.html#aa6207c8cf9a3e442f153dc0241aea600a1c147538fd896f4f9abce9eaea9727e3">Mat::AUTO_STEP</a>)</td></tr>
<tr class="memdesc:ab7210166f4bd124855b520b3dde28fb1"><td class="mdescLeft"> </td><td class="mdescRight">constructor for <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> headers pointing to user-allocated data  <a href="#ab7210166f4bd124855b520b3dde28fb1">More...</a><br/></td></tr>
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<tr class="memitem:a658d498dbb3ecff8bacb52934862533d"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a658d498dbb3ecff8bacb52934862533d">GpuMat</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab02f97698d8272f0d253f3029329ed10">size</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>, void *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a5139f9492f9079c7b9e414d50da332a3">data</a>, size_t <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af46427ea4c9b3fe7687e3afa84baede3">step</a>=<a class="el" href="../../d3/d63/classcv_1_1Mat.html#aa6207c8cf9a3e442f153dc0241aea600a1c147538fd896f4f9abce9eaea9727e3">Mat::AUTO_STEP</a>)</td></tr>
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<tr class="memitem:acb11621e15a3e06d243b73ae04a0f398"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#acb11621e15a3e06d243b73ae04a0f398">GpuMat</a> (const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp;m, <a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a0bf9a88fc518cc9986808aaf916f2182">rowRange</a>, <a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7256892911593daf1bdefb183d6fd29e">colRange</a>)</td></tr>
<tr class="memdesc:acb11621e15a3e06d243b73ae04a0f398"><td class="mdescLeft"> </td><td class="mdescRight">creates a <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for a part of the bigger matrix  <a href="#acb11621e15a3e06d243b73ae04a0f398">More...</a><br/></td></tr>
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<tr class="memitem:aed4eea5d06f115f2a137822cb11cea46"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#aed4eea5d06f115f2a137822cb11cea46">GpuMat</a> (const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp;m, <a class="el" href="../../dc/d84/group__core__basic.html#ga11d95de507098e90bad732b9345402e8">Rect</a> roi)</td></tr>
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<tr class="memitem:a28fd93f7aa3adbcadd9c1f7f7d87bb4c"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a28fd93f7aa3adbcadd9c1f7f7d87bb4c">GpuMat</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> arr, <a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a>=<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>())</td></tr>
<tr class="memdesc:a28fd93f7aa3adbcadd9c1f7f7d87bb4c"><td class="mdescLeft"> </td><td class="mdescRight">builds <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> from host memory (Blocking call)  <a href="#a28fd93f7aa3adbcadd9c1f7f7d87bb4c">More...</a><br/></td></tr>
<tr class="separator:a28fd93f7aa3adbcadd9c1f7f7d87bb4c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a576b5879eff288bdc3364b6123e38457"><td align="right" class="memItemLeft" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a576b5879eff288bdc3364b6123e38457">~GpuMat</a> ()</td></tr>
<tr class="memdesc:a576b5879eff288bdc3364b6123e38457"><td class="mdescLeft"> </td><td class="mdescRight">destructor - calls <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a460951a00945774e9da0b1062ea0a319" title="decreases reference counter, deallocate the data when reference counter reaches 0 ...">release()</a>  <a href="#a576b5879eff288bdc3364b6123e38457">More...</a><br/></td></tr>
<tr class="separator:a576b5879eff288bdc3364b6123e38457"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ae01becaff20100678a2fca4fce4dd975"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ae01becaff20100678a2fca4fce4dd975">adjustROI</a> (int dtop, int dbottom, int dleft, int dright)</td></tr>
<tr class="memdesc:ae01becaff20100678a2fca4fce4dd975"><td class="mdescLeft"> </td><td class="mdescRight">moves/resizes the current <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> ROI inside the parent <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a>  <a href="#ae01becaff20100678a2fca4fce4dd975">More...</a><br/></td></tr>
<tr class="separator:ae01becaff20100678a2fca4fce4dd975"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a03e76eb8993215020cff624ace66d7e6"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a03e76eb8993215020cff624ace66d7e6">assignTo</a> (<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp;m, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>=-1) const</td></tr>
<tr class="separator:a03e76eb8993215020cff624ace66d7e6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a538fc6d75281b4ecb7ad50e4555f3fc6"><td align="right" class="memItemLeft" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a538fc6d75281b4ecb7ad50e4555f3fc6">channels</a> () const</td></tr>
<tr class="memdesc:a538fc6d75281b4ecb7ad50e4555f3fc6"><td class="mdescLeft"> </td><td class="mdescRight">returns number of channels  <a href="#a538fc6d75281b4ecb7ad50e4555f3fc6">More...</a><br/></td></tr>
<tr class="separator:a538fc6d75281b4ecb7ad50e4555f3fc6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ae1d42819f7f3251478cd6edab8069758"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ae1d42819f7f3251478cd6edab8069758">clone</a> () const</td></tr>
<tr class="memdesc:ae1d42819f7f3251478cd6edab8069758"><td class="mdescLeft"> </td><td class="mdescRight">returns deep copy of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a>, i.e. the data is copied  <a href="#ae1d42819f7f3251478cd6edab8069758">More...</a><br/></td></tr>
<tr class="separator:ae1d42819f7f3251478cd6edab8069758"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aac2b18c2ef3fbefc6f776cc313b966c0"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#aac2b18c2ef3fbefc6f776cc313b966c0">col</a> (int x) const</td></tr>
<tr class="memdesc:aac2b18c2ef3fbefc6f776cc313b966c0"><td class="mdescLeft"> </td><td class="mdescRight">returns a new <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for the specified column  <a href="#aac2b18c2ef3fbefc6f776cc313b966c0">More...</a><br/></td></tr>
<tr class="separator:aac2b18c2ef3fbefc6f776cc313b966c0"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a7256892911593daf1bdefb183d6fd29e"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7256892911593daf1bdefb183d6fd29e">colRange</a> (int startcol, int endcol) const</td></tr>
<tr class="memdesc:a7256892911593daf1bdefb183d6fd29e"><td class="mdescLeft"> </td><td class="mdescRight">... for the specified column span  <a href="#a7256892911593daf1bdefb183d6fd29e">More...</a><br/></td></tr>
<tr class="separator:a7256892911593daf1bdefb183d6fd29e"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:acfcbd3a61ca20ec908dc6de76ef6e5bb"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#acfcbd3a61ca20ec908dc6de76ef6e5bb">colRange</a> (<a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> r) const</td></tr>
<tr class="separator:acfcbd3a61ca20ec908dc6de76ef6e5bb"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a3a1b076e54d8a8503014e27a5440d98a"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a3a1b076e54d8a8503014e27a5440d98a">convertTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, int rtype) const</td></tr>
<tr class="memdesc:a3a1b076e54d8a8503014e27a5440d98a"><td class="mdescLeft"> </td><td class="mdescRight">converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype (Blocking call)  <a href="#a3a1b076e54d8a8503014e27a5440d98a">More...</a><br/></td></tr>
<tr class="separator:a3a1b076e54d8a8503014e27a5440d98a"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a079d3d6541bb2fe6127c8f5d58953c9c"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a079d3d6541bb2fe6127c8f5d58953c9c">convertTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, int rtype, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream) const</td></tr>
<tr class="memdesc:a079d3d6541bb2fe6127c8f5d58953c9c"><td class="mdescLeft"> </td><td class="mdescRight">converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype (Non-Blocking call)  <a href="#a079d3d6541bb2fe6127c8f5d58953c9c">More...</a><br/></td></tr>
<tr class="separator:a079d3d6541bb2fe6127c8f5d58953c9c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a656ac1f6a1426527f838c19e2d677dc0"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a656ac1f6a1426527f838c19e2d677dc0">convertTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, int rtype, double alpha, double beta=0.0) const</td></tr>
<tr class="memdesc:a656ac1f6a1426527f838c19e2d677dc0"><td class="mdescLeft"> </td><td class="mdescRight">converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype with scaling (Blocking call)  <a href="#a656ac1f6a1426527f838c19e2d677dc0">More...</a><br/></td></tr>
<tr class="separator:a656ac1f6a1426527f838c19e2d677dc0"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a54f6bde0a55552bc80a48ecbc8e272d6"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a54f6bde0a55552bc80a48ecbc8e272d6">convertTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, int rtype, double alpha, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream) const</td></tr>
<tr class="memdesc:a54f6bde0a55552bc80a48ecbc8e272d6"><td class="mdescLeft"> </td><td class="mdescRight">converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype with scaling (Non-Blocking call)  <a href="#a54f6bde0a55552bc80a48ecbc8e272d6">More...</a><br/></td></tr>
<tr class="separator:a54f6bde0a55552bc80a48ecbc8e272d6"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a408e9ba5344ab7d3aa27323774de118e"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a408e9ba5344ab7d3aa27323774de118e">convertTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, int rtype, double alpha, double beta, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream) const</td></tr>
<tr class="memdesc:a408e9ba5344ab7d3aa27323774de118e"><td class="mdescLeft"> </td><td class="mdescRight">converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype with scaling (Non-Blocking call)  <a href="#a408e9ba5344ab7d3aa27323774de118e">More...</a><br/></td></tr>
<tr class="separator:a408e9ba5344ab7d3aa27323774de118e"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a948c562ee340c0678a44884bde1f5a3e"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a948c562ee340c0678a44884bde1f5a3e">copyTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst) const</td></tr>
<tr class="memdesc:a948c562ee340c0678a44884bde1f5a3e"><td class="mdescLeft"> </td><td class="mdescRight">copies the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> content to device memory (Blocking call)  <a href="#a948c562ee340c0678a44884bde1f5a3e">More...</a><br/></td></tr>
<tr class="separator:a948c562ee340c0678a44884bde1f5a3e"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:adf64af21a2bb13276269584c2a6e1b81"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#adf64af21a2bb13276269584c2a6e1b81">copyTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream) const</td></tr>
<tr class="memdesc:adf64af21a2bb13276269584c2a6e1b81"><td class="mdescLeft"> </td><td class="mdescRight">copies the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> content to device memory (Non-Blocking call)  <a href="#adf64af21a2bb13276269584c2a6e1b81">More...</a><br/></td></tr>
<tr class="separator:adf64af21a2bb13276269584c2a6e1b81"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad47f7b0aaf53fa904a6381e7d0192145"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad47f7b0aaf53fa904a6381e7d0192145">copyTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, <a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> mask) const</td></tr>
<tr class="memdesc:ad47f7b0aaf53fa904a6381e7d0192145"><td class="mdescLeft"> </td><td class="mdescRight">copies those <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to "m" that are marked with non-zero mask elements (Blocking call)  <a href="#ad47f7b0aaf53fa904a6381e7d0192145">More...</a><br/></td></tr>
<tr class="separator:ad47f7b0aaf53fa904a6381e7d0192145"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a49b74a0ef2076543de438fadde55de7b"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a49b74a0ef2076543de438fadde55de7b">copyTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, <a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> mask, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream) const</td></tr>
<tr class="memdesc:a49b74a0ef2076543de438fadde55de7b"><td class="mdescLeft"> </td><td class="mdescRight">copies those <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to "m" that are marked with non-zero mask elements (Non-Blocking call)  <a href="#a49b74a0ef2076543de438fadde55de7b">More...</a><br/></td></tr>
<tr class="separator:a49b74a0ef2076543de438fadde55de7b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af21454929f3efba4c783edbc27042200"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af21454929f3efba4c783edbc27042200">create</a> (int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7385022ca9114e5f5058dbb2f12467cb">rows</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a9265a32d8d29fe29804a0cb8f57213e9">cols</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>)</td></tr>
<tr class="memdesc:af21454929f3efba4c783edbc27042200"><td class="mdescLeft"> </td><td class="mdescRight">allocates new <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> data unless the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> already has specified size and type  <a href="#af21454929f3efba4c783edbc27042200">More...</a><br/></td></tr>
<tr class="separator:af21454929f3efba4c783edbc27042200"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af88f29d92f6fc2c29cd6ff8960954d4e"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af88f29d92f6fc2c29cd6ff8960954d4e">create</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab02f97698d8272f0d253f3029329ed10">size</a>, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a>)</td></tr>
<tr class="separator:af88f29d92f6fc2c29cd6ff8960954d4e"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:abd47c99304aa165d2214ce9991313bdd"><td align="right" class="memItemLeft" valign="top">void * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#abd47c99304aa165d2214ce9991313bdd">cudaPtr</a> () const</td></tr>
<tr class="separator:abd47c99304aa165d2214ce9991313bdd"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aaa229d9b2b2f60ecae3b5fbf0603c1b9"><td align="right" class="memItemLeft" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#aaa229d9b2b2f60ecae3b5fbf0603c1b9">depth</a> () const</td></tr>
<tr class="memdesc:aaa229d9b2b2f60ecae3b5fbf0603c1b9"><td class="mdescLeft"> </td><td class="mdescRight">returns element type  <a href="#aaa229d9b2b2f60ecae3b5fbf0603c1b9">More...</a><br/></td></tr>
<tr class="separator:aaa229d9b2b2f60ecae3b5fbf0603c1b9"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a027e74e4364ddfd9687b58aa5db8d4e8"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a027e74e4364ddfd9687b58aa5db8d4e8">download</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst) const</td></tr>
<tr class="memdesc:a027e74e4364ddfd9687b58aa5db8d4e8"><td class="mdescLeft"> </td><td class="mdescRight">Performs data download from <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Blocking call)  <a href="#a027e74e4364ddfd9687b58aa5db8d4e8">More...</a><br/></td></tr>
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<tr class="memitem:a2522fd0642c30e0455ec52a28bd3be7b"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a2522fd0642c30e0455ec52a28bd3be7b">download</a> (<a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> dst, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream) const</td></tr>
<tr class="memdesc:a2522fd0642c30e0455ec52a28bd3be7b"><td class="mdescLeft"> </td><td class="mdescRight">Performs data download from <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Non-Blocking call)  <a href="#a2522fd0642c30e0455ec52a28bd3be7b">More...</a><br/></td></tr>
<tr class="separator:a2522fd0642c30e0455ec52a28bd3be7b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a7e73b4fa94d32e0585564217ebe3fc6c"><td align="right" class="memItemLeft" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7e73b4fa94d32e0585564217ebe3fc6c">elemSize</a> () const</td></tr>
<tr class="memdesc:a7e73b4fa94d32e0585564217ebe3fc6c"><td class="mdescLeft"> </td><td class="mdescRight">returns element size in bytes  <a href="#a7e73b4fa94d32e0585564217ebe3fc6c">More...</a><br/></td></tr>
<tr class="separator:a7e73b4fa94d32e0585564217ebe3fc6c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a988831407704239eadc036df1b615de5"><td align="right" class="memItemLeft" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a988831407704239eadc036df1b615de5">elemSize1</a> () const</td></tr>
<tr class="memdesc:a988831407704239eadc036df1b615de5"><td class="mdescLeft"> </td><td class="mdescRight">returns the size of element channel in bytes  <a href="#a988831407704239eadc036df1b615de5">More...</a><br/></td></tr>
<tr class="separator:a988831407704239eadc036df1b615de5"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a509710f61e3a7e13b5ebb2b40984900a"><td align="right" class="memItemLeft" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a509710f61e3a7e13b5ebb2b40984900a">empty</a> () const</td></tr>
<tr class="memdesc:a509710f61e3a7e13b5ebb2b40984900a"><td class="mdescLeft"> </td><td class="mdescRight">returns true if <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> data is NULL  <a href="#a509710f61e3a7e13b5ebb2b40984900a">More...</a><br/></td></tr>
<tr class="separator:a509710f61e3a7e13b5ebb2b40984900a"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a400fc4c7880bf132f2ffea03892486b0"><td align="right" class="memItemLeft" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a400fc4c7880bf132f2ffea03892486b0">isContinuous</a> () const</td></tr>
<tr class="separator:a400fc4c7880bf132f2ffea03892486b0"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a934d25560bfb1f03c0077e437d41e0cb"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a934d25560bfb1f03c0077e437d41e0cb">locateROI</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> &amp;wholeSize, <a class="el" href="../../dc/d84/group__core__basic.html#ga1e83eafb2d26b3c93f09e8338bcab192">Point</a> &amp;ofs) const</td></tr>
<tr class="memdesc:a934d25560bfb1f03c0077e437d41e0cb"><td class="mdescLeft"> </td><td class="mdescRight">locates <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header within a parent <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a>  <a href="#a934d25560bfb1f03c0077e437d41e0cb">More...</a><br/></td></tr>
<tr class="separator:a934d25560bfb1f03c0077e437d41e0cb"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a8b0aa2f9bdf8b40f43be8d8068f2e389"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a8b0aa2f9bdf8b40f43be8d8068f2e389"><td align="right" class="memTemplItemLeft" valign="top"> </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a8b0aa2f9bdf8b40f43be8d8068f2e389">operator PtrStep&lt; _Tp &gt;</a> () const</td></tr>
<tr class="separator:a8b0aa2f9bdf8b40f43be8d8068f2e389"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a939f8ef4be2fc9a51058c2404d491f74"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a939f8ef4be2fc9a51058c2404d491f74"><td align="right" class="memTemplItemLeft" valign="top"> </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a939f8ef4be2fc9a51058c2404d491f74">operator PtrStepSz&lt; _Tp &gt;</a> () const</td></tr>
<tr class="separator:a939f8ef4be2fc9a51058c2404d491f74"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a2b3c25e36b0f82ca8f9f74b6ae68c41d"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a2b3c25e36b0f82ca8f9f74b6ae68c41d">operator()</a> (<a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a0bf9a88fc518cc9986808aaf916f2182">rowRange</a>, <a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7256892911593daf1bdefb183d6fd29e">colRange</a>) const</td></tr>
<tr class="memdesc:a2b3c25e36b0f82ca8f9f74b6ae68c41d"><td class="mdescLeft"> </td><td class="mdescRight">extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.)  <a href="#a2b3c25e36b0f82ca8f9f74b6ae68c41d">More...</a><br/></td></tr>
<tr class="separator:a2b3c25e36b0f82ca8f9f74b6ae68c41d"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a217e27e7051bed168c34ba767915cc63"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a217e27e7051bed168c34ba767915cc63">operator()</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga11d95de507098e90bad732b9345402e8">Rect</a> roi) const</td></tr>
<tr class="separator:a217e27e7051bed168c34ba767915cc63"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad1432eed28a34f995a641a296281e01c"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad1432eed28a34f995a641a296281e01c">operator=</a> (const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp;m)</td></tr>
<tr class="memdesc:ad1432eed28a34f995a641a296281e01c"><td class="mdescLeft"> </td><td class="mdescRight">assignment operators  <a href="#ad1432eed28a34f995a641a296281e01c">More...</a><br/></td></tr>
<tr class="separator:ad1432eed28a34f995a641a296281e01c"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aa83fa0825c60eb22a11a87a98c3cd5ed"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#aa83fa0825c60eb22a11a87a98c3cd5ed">ptr</a> (int y=0)</td></tr>
<tr class="memdesc:aa83fa0825c60eb22a11a87a98c3cd5ed"><td class="mdescLeft"> </td><td class="mdescRight">returns pointer to y-th row  <a href="#aa83fa0825c60eb22a11a87a98c3cd5ed">More...</a><br/></td></tr>
<tr class="separator:aa83fa0825c60eb22a11a87a98c3cd5ed"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad95918b9342332a41a584b21134b0959"><td align="right" class="memItemLeft" valign="top">const <a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad95918b9342332a41a584b21134b0959">ptr</a> (int y=0) const</td></tr>
<tr class="separator:ad95918b9342332a41a584b21134b0959"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af0389962003eec644007c7ca85a04f6d"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:af0389962003eec644007c7ca85a04f6d"><td align="right" class="memTemplItemLeft" valign="top">_Tp * </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af0389962003eec644007c7ca85a04f6d">ptr</a> (int y=0)</td></tr>
<tr class="memdesc:af0389962003eec644007c7ca85a04f6d"><td class="mdescLeft"> </td><td class="mdescRight">template version of the above method  <a href="#af0389962003eec644007c7ca85a04f6d">More...</a><br/></td></tr>
<tr class="separator:af0389962003eec644007c7ca85a04f6d"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a2d7003ff9fa0a24c5e4986174c29820f"><td class="memTemplParams" colspan="2">template&lt;typename _Tp &gt; </td></tr>
<tr class="memitem:a2d7003ff9fa0a24c5e4986174c29820f"><td align="right" class="memTemplItemLeft" valign="top">const _Tp * </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a2d7003ff9fa0a24c5e4986174c29820f">ptr</a> (int y=0) const</td></tr>
<tr class="separator:a2d7003ff9fa0a24c5e4986174c29820f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a460951a00945774e9da0b1062ea0a319"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a460951a00945774e9da0b1062ea0a319">release</a> ()</td></tr>
<tr class="memdesc:a460951a00945774e9da0b1062ea0a319"><td class="mdescLeft"> </td><td class="mdescRight">decreases reference counter, deallocate the data when reference counter reaches 0  <a href="#a460951a00945774e9da0b1062ea0a319">More...</a><br/></td></tr>
<tr class="separator:a460951a00945774e9da0b1062ea0a319"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a408e22ed824d1ddf59f58bda895017a8"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a408e22ed824d1ddf59f58bda895017a8">reshape</a> (int cn, int <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7385022ca9114e5f5058dbb2f12467cb">rows</a>=0) const</td></tr>
<tr class="separator:a408e22ed824d1ddf59f58bda895017a8"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a8d6954870e3c3eacc0ea85cd38bd86b4"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a8d6954870e3c3eacc0ea85cd38bd86b4">row</a> (int y) const</td></tr>
<tr class="memdesc:a8d6954870e3c3eacc0ea85cd38bd86b4"><td class="mdescLeft"> </td><td class="mdescRight">returns a new <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for the specified row  <a href="#a8d6954870e3c3eacc0ea85cd38bd86b4">More...</a><br/></td></tr>
<tr class="separator:a8d6954870e3c3eacc0ea85cd38bd86b4"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a0bf9a88fc518cc9986808aaf916f2182"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a0bf9a88fc518cc9986808aaf916f2182">rowRange</a> (int startrow, int endrow) const</td></tr>
<tr class="memdesc:a0bf9a88fc518cc9986808aaf916f2182"><td class="mdescLeft"> </td><td class="mdescRight">... for the specified row span  <a href="#a0bf9a88fc518cc9986808aaf916f2182">More...</a><br/></td></tr>
<tr class="separator:a0bf9a88fc518cc9986808aaf916f2182"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aabccb49164b02284e26884360b7062e8"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#aabccb49164b02284e26884360b7062e8">rowRange</a> (<a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> r) const</td></tr>
<tr class="separator:aabccb49164b02284e26884360b7062e8"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab263999dea4f7f28d4dd4ced6d2e970b"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab263999dea4f7f28d4dd4ced6d2e970b">setTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> s)</td></tr>
<tr class="memdesc:ab263999dea4f7f28d4dd4ced6d2e970b"><td class="mdescLeft"> </td><td class="mdescRight">sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s (Blocking call)  <a href="#ab263999dea4f7f28d4dd4ced6d2e970b">More...</a><br/></td></tr>
<tr class="separator:ab263999dea4f7f28d4dd4ced6d2e970b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:aa155961a4c8c19bdb2c9b1886e45ce9a"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#aa155961a4c8c19bdb2c9b1886e45ce9a">setTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> s, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream)</td></tr>
<tr class="memdesc:aa155961a4c8c19bdb2c9b1886e45ce9a"><td class="mdescLeft"> </td><td class="mdescRight">sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s (Non-Blocking call)  <a href="#aa155961a4c8c19bdb2c9b1886e45ce9a">More...</a><br/></td></tr>
<tr class="separator:aa155961a4c8c19bdb2c9b1886e45ce9a"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a16cb9be32213df86f3b55ec131abff70"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a16cb9be32213df86f3b55ec131abff70">setTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> s, <a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> mask)</td></tr>
<tr class="memdesc:a16cb9be32213df86f3b55ec131abff70"><td class="mdescLeft"> </td><td class="mdescRight">sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s, according to the mask (Blocking call)  <a href="#a16cb9be32213df86f3b55ec131abff70">More...</a><br/></td></tr>
<tr class="separator:a16cb9be32213df86f3b55ec131abff70"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a1090e7ff25e23cf6243809e9a031b51d"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1090e7ff25e23cf6243809e9a031b51d">setTo</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> s, <a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> mask, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream)</td></tr>
<tr class="memdesc:a1090e7ff25e23cf6243809e9a031b51d"><td class="mdescLeft"> </td><td class="mdescRight">sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s, according to the mask (Non-Blocking call)  <a href="#a1090e7ff25e23cf6243809e9a031b51d">More...</a><br/></td></tr>
<tr class="separator:a1090e7ff25e23cf6243809e9a031b51d"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab02f97698d8272f0d253f3029329ed10"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab02f97698d8272f0d253f3029329ed10">size</a> () const</td></tr>
<tr class="memdesc:ab02f97698d8272f0d253f3029329ed10"><td class="mdescLeft"> </td><td class="mdescRight">returns <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> size : width == number of columns, height == number of rows  <a href="#ab02f97698d8272f0d253f3029329ed10">More...</a><br/></td></tr>
<tr class="separator:ab02f97698d8272f0d253f3029329ed10"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a5ead91d096cca20e59ba9af8574187cc"><td align="right" class="memItemLeft" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a5ead91d096cca20e59ba9af8574187cc">step1</a> () const</td></tr>
<tr class="memdesc:a5ead91d096cca20e59ba9af8574187cc"><td class="mdescLeft"> </td><td class="mdescRight">returns step/elemSize1()  <a href="#a5ead91d096cca20e59ba9af8574187cc">More...</a><br/></td></tr>
<tr class="separator:a5ead91d096cca20e59ba9af8574187cc"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a7135c058aef51c37884a2b2ae8151631"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7135c058aef51c37884a2b2ae8151631">swap</a> (<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp;mat)</td></tr>
<tr class="memdesc:a7135c058aef51c37884a2b2ae8151631"><td class="mdescLeft"> </td><td class="mdescRight">swaps with other smart pointer  <a href="#a7135c058aef51c37884a2b2ae8151631">More...</a><br/></td></tr>
<tr class="separator:a7135c058aef51c37884a2b2ae8151631"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ab0c835e86e2af3c8fc14fee8a2937281"><td align="right" class="memItemLeft" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ab0c835e86e2af3c8fc14fee8a2937281">type</a> () const</td></tr>
<tr class="memdesc:ab0c835e86e2af3c8fc14fee8a2937281"><td class="mdescLeft"> </td><td class="mdescRight">returns element type  <a href="#ab0c835e86e2af3c8fc14fee8a2937281">More...</a><br/></td></tr>
<tr class="separator:ab0c835e86e2af3c8fc14fee8a2937281"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a700ad759547d8c4255833e1fa0e6f751"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a700ad759547d8c4255833e1fa0e6f751">updateContinuityFlag</a> ()</td></tr>
<tr class="memdesc:a700ad759547d8c4255833e1fa0e6f751"><td class="mdescLeft"> </td><td class="mdescRight">internal use method: updates the continuity flag  <a href="#a700ad759547d8c4255833e1fa0e6f751">More...</a><br/></td></tr>
<tr class="separator:a700ad759547d8c4255833e1fa0e6f751"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a00ef5bfe18d14623dcf578a35e40a46b"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a00ef5bfe18d14623dcf578a35e40a46b">upload</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> arr)</td></tr>
<tr class="memdesc:a00ef5bfe18d14623dcf578a35e40a46b"><td class="mdescLeft"> </td><td class="mdescRight">Performs data upload to <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Blocking call)  <a href="#a00ef5bfe18d14623dcf578a35e40a46b">More...</a><br/></td></tr>
<tr class="separator:a00ef5bfe18d14623dcf578a35e40a46b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a89d1f885b9f5a479a7c4eb319e7368ae"><td align="right" class="memItemLeft" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a89d1f885b9f5a479a7c4eb319e7368ae">upload</a> (<a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> arr, <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp;stream)</td></tr>
<tr class="memdesc:a89d1f885b9f5a479a7c4eb319e7368ae"><td class="mdescLeft"> </td><td class="mdescRight">Performs data upload to <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Non-Blocking call)  <a href="#a89d1f885b9f5a479a7c4eb319e7368ae">More...</a><br/></td></tr>
<tr class="separator:a89d1f885b9f5a479a7c4eb319e7368ae"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:ad3e0ed263377f0989c3490f3d496a201"><td align="right" class="memItemLeft" valign="top">static <a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">defaultAllocator</a> ()</td></tr>
<tr class="memdesc:ad3e0ed263377f0989c3490f3d496a201"><td class="mdescLeft"> </td><td class="mdescRight">default allocator  <a href="#ad3e0ed263377f0989c3490f3d496a201">More...</a><br/></td></tr>
<tr class="separator:ad3e0ed263377f0989c3490f3d496a201"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a5cc463cf6516957a2d78bd03c6d81de5"><td align="right" class="memItemLeft" valign="top">static void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a5cc463cf6516957a2d78bd03c6d81de5">setDefaultAllocator</a> (<a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> *<a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a>)</td></tr>
<tr class="separator:a5cc463cf6516957a2d78bd03c6d81de5"><td class="memSeparator" colspan="2"> </td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-attribs"></a>
Public Attributes</h2></td></tr>
<tr class="memitem:a1dc1f7a23c89d2a36f0efc7db1b0d5a4"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">Allocator</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">allocator</a></td></tr>
<tr class="memdesc:a1dc1f7a23c89d2a36f0efc7db1b0d5a4"><td class="mdescLeft"> </td><td class="mdescRight">allocator  <a href="#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">More...</a><br/></td></tr>
<tr class="separator:a1dc1f7a23c89d2a36f0efc7db1b0d5a4"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a9265a32d8d29fe29804a0cb8f57213e9"><td align="right" class="memItemLeft" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a9265a32d8d29fe29804a0cb8f57213e9">cols</a></td></tr>
<tr class="separator:a9265a32d8d29fe29804a0cb8f57213e9"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a5139f9492f9079c7b9e414d50da332a3"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a5139f9492f9079c7b9e414d50da332a3">data</a></td></tr>
<tr class="memdesc:a5139f9492f9079c7b9e414d50da332a3"><td class="mdescLeft"> </td><td class="mdescRight">pointer to the data  <a href="#a5139f9492f9079c7b9e414d50da332a3">More...</a><br/></td></tr>
<tr class="separator:a5139f9492f9079c7b9e414d50da332a3"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ad76c4f58490134f1acf3e580e669c58b"><td align="right" class="memItemLeft" valign="top">const <a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad76c4f58490134f1acf3e580e669c58b">dataend</a></td></tr>
<tr class="separator:ad76c4f58490134f1acf3e580e669c58b"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ade4a4dfc61facd5f18143b4c9d56dbae"><td align="right" class="memItemLeft" valign="top"><a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a> * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ade4a4dfc61facd5f18143b4c9d56dbae">datastart</a></td></tr>
<tr class="memdesc:ade4a4dfc61facd5f18143b4c9d56dbae"><td class="mdescLeft"> </td><td class="mdescRight">helper fields used in locateROI and adjustROI  <a href="#ade4a4dfc61facd5f18143b4c9d56dbae">More...</a><br/></td></tr>
<tr class="separator:ade4a4dfc61facd5f18143b4c9d56dbae"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:adfd242b365e79ebc382a0829d8e9f44f"><td align="right" class="memItemLeft" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#adfd242b365e79ebc382a0829d8e9f44f">flags</a></td></tr>
<tr class="separator:adfd242b365e79ebc382a0829d8e9f44f"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af528e8b675a72fd79ff1f399b7dd42df"><td align="right" class="memItemLeft" valign="top">int * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af528e8b675a72fd79ff1f399b7dd42df">refcount</a></td></tr>
<tr class="separator:af528e8b675a72fd79ff1f399b7dd42df"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a7385022ca9114e5f5058dbb2f12467cb"><td align="right" class="memItemLeft" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a7385022ca9114e5f5058dbb2f12467cb">rows</a></td></tr>
<tr class="memdesc:a7385022ca9114e5f5058dbb2f12467cb"><td class="mdescLeft"> </td><td class="mdescRight">the number of rows and columns  <a href="#a7385022ca9114e5f5058dbb2f12467cb">More...</a><br/></td></tr>
<tr class="separator:a7385022ca9114e5f5058dbb2f12467cb"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:af46427ea4c9b3fe7687e3afa84baede3"><td align="right" class="memItemLeft" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#af46427ea4c9b3fe7687e3afa84baede3">step</a></td></tr>
<tr class="memdesc:af46427ea4c9b3fe7687e3afa84baede3"><td class="mdescLeft"> </td><td class="mdescRight">a distance between successive rows in bytes; includes the gap if any  <a href="#af46427ea4c9b3fe7687e3afa84baede3">More...</a><br/></td></tr>
<tr class="separator:af46427ea4c9b3fe7687e3afa84baede3"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<a id="details" name="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Base storage class for GPU memory with reference counting. </p>
<p>Its interface matches the <a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a> interface with the following limitations:</p>
<ul>
<li>no arbitrary dimensions support (only 2D)</li>
<li>no functions that return references to their data (because references on GPU are not valid for CPU)</li>
<li>no expression templates technique support</li>
</ul>
<p>Beware that the latter limitation may lead to overloaded matrix operators that cause memory allocations. The <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> class is convertible to cuda::PtrStepSz and cuda::PtrStep so it can be passed directly to the kernel.</p>
<dl class="section note"><dt>Note</dt><dd>In contrast with <a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a>, in most cases <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a400fc4c7880bf132f2ffea03892486b0">GpuMat::isContinuous()</a> == false . This means that rows are aligned to a size depending on the hardware. Single-row <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> is always a continuous matrix.</dd>
<dd>
You are not recommended to leave static or global <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> variables allocated, that is, to rely on its destructor. The destruction order of such variables and CUDA context is undefined. GPU memory release function returns error if the CUDA context has been destroyed before.</dd></dl>
<p>Some member functions are described as a "Blocking Call" while some are described as a "Non-Blocking Call". Blocking functions are synchronous to host. It is guaranteed that the GPU operation is finished when the function returns. However, non-blocking functions are asynchronous to host. Those functions may return even if the GPU operation is not finished.</p>
<p>Compared to their blocking counterpart, non-blocking functions accept <a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html" title="This class encapsulates a queue of asynchronous calls. ">Stream</a> as an additional argument. If a non-default stream is passed, the GPU operation may overlap with operations in other streams.</p>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="../../d3/d63/classcv_1_1Mat.html" title="n-dimensional dense array class ">Mat</a> </dd></dl>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a1ac7380bd407013cc35b150f6243c417"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1ac7380bd407013cc35b150f6243c417">◆ </a></span>GpuMat() <span class="overload">[1/11]</span></h2>
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<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
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          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em> = <code><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>()</code></td><td>)</td>
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  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">explicit</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>default constructor </p>
</div>
</div>
<a id="ac93af62c4de452d69e61c0adef511429"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac93af62c4de452d69e61c0adef511429">◆ </a></span>GpuMat() <span class="overload">[2/11]</span></h2>
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          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em>, </td>
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          <td class="paramtype">int </td>
          <td class="paramname"><em>cols</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em> = <code><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>()</code> </td>
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          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>constructs <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> of the specified size and type </p>
</div>
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<h2 class="memtitle"><span class="permalink"><a href="#a36a4b321e7b141f99d41c0b431f74c5e">◆ </a></span>GpuMat() <span class="overload">[3/11]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td>
          <td class="paramname"><em>size</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em> = <code><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>()</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="a40333be65edc1191260d1f7252b0d72c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a40333be65edc1191260d1f7252b0d72c">◆ </a></span>GpuMat() <span class="overload">[4/11]</span></h2>
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      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>cols</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> </td>
          <td class="paramname"><em>s</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em> = <code><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>()</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>constructs <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> and fills it with the specified value _s </p>
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<a id="a378bc9ca64dcbbb3dacef9fe48e9c0a5"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a378bc9ca64dcbbb3dacef9fe48e9c0a5">◆ </a></span>GpuMat() <span class="overload">[5/11]</span></h2>
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      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td>
          <td class="paramname"><em>size</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> </td>
          <td class="paramname"><em>s</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em> = <code><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>()</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="af1fd1025a62d333c9c970ca3761a23db"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af1fd1025a62d333c9c970ca3761a23db">◆ </a></span>GpuMat() <span class="overload">[6/11]</span></h2>
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          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype">const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td>
          <td class="paramname"><em>m</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>copy constructor </p>
</div>
</div>
<a id="ab7210166f4bd124855b520b3dde28fb1"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab7210166f4bd124855b520b3dde28fb1">◆ </a></span>GpuMat() <span class="overload">[7/11]</span></h2>
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      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>cols</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">void * </td>
          <td class="paramname"><em>data</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">size_t </td>
          <td class="paramname"><em>step</em> = <code><a class="el" href="../../d3/d63/classcv_1_1Mat.html#aa6207c8cf9a3e442f153dc0241aea600a1c147538fd896f4f9abce9eaea9727e3">Mat::AUTO_STEP</a></code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>constructor for <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> headers pointing to user-allocated data </p>
</div>
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<a id="a658d498dbb3ecff8bacb52934862533d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a658d498dbb3ecff8bacb52934862533d">◆ </a></span>GpuMat() <span class="overload">[8/11]</span></h2>
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        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td>
          <td class="paramname"><em>size</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">void * </td>
          <td class="paramname"><em>data</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">size_t </td>
          <td class="paramname"><em>step</em> = <code><a class="el" href="../../d3/d63/classcv_1_1Mat.html#aa6207c8cf9a3e442f153dc0241aea600a1c147538fd896f4f9abce9eaea9727e3">Mat::AUTO_STEP</a></code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="acb11621e15a3e06d243b73ae04a0f398"></a>
<h2 class="memtitle"><span class="permalink"><a href="#acb11621e15a3e06d243b73ae04a0f398">◆ </a></span>GpuMat() <span class="overload">[9/11]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype">const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td>
          <td class="paramname"><em>m</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> </td>
          <td class="paramname"><em>rowRange</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> </td>
          <td class="paramname"><em>colRange</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>creates a <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for a part of the bigger matrix </p>
</div>
</div>
<a id="aed4eea5d06f115f2a137822cb11cea46"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aed4eea5d06f115f2a137822cb11cea46">◆ </a></span>GpuMat() <span class="overload">[10/11]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype">const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td>
          <td class="paramname"><em>m</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga11d95de507098e90bad732b9345402e8">Rect</a> </td>
          <td class="paramname"><em>roi</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="a28fd93f7aa3adbcadd9c1f7f7d87bb4c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a28fd93f7aa3adbcadd9c1f7f7d87bb4c">◆ </a></span>GpuMat() <span class="overload">[11/11]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::GpuMat </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>arr</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em> = <code><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#ad3e0ed263377f0989c3490f3d496a201">GpuMat::defaultAllocator</a>()</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">explicit</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">rows, cols, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">size, type, s[, allocator]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, rowRange, colRange</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">m, roi</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>&lt;cuda_GpuMat object&gt;</td><td>=</td><td>cv.cuda_GpuMat(</td><td class="paramname">arr[, allocator]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>builds <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> from host memory (Blocking call) </p>
</div>
</div>
<a id="a576b5879eff288bdc3364b6123e38457"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a576b5879eff288bdc3364b6123e38457">◆ </a></span>~GpuMat()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::~GpuMat </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">
<p>destructor - calls <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html#a460951a00945774e9da0b1062ea0a319" title="decreases reference counter, deallocate the data when reference counter reaches 0 ...">release()</a> </p>
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="ae01becaff20100678a2fca4fce4dd975"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ae01becaff20100678a2fca4fce4dd975">◆ </a></span>adjustROI()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a>&amp; cv::cuda::GpuMat::adjustROI </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>dtop</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>dbottom</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>dleft</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>dright</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.adjustROI(</td><td class="paramname">dtop, dbottom, dleft, dright</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>moves/resizes the current <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> ROI inside the parent <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> </p>
</div>
</div>
<a id="a03e76eb8993215020cff624ace66d7e6"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a03e76eb8993215020cff624ace66d7e6">◆ </a></span>assignTo()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::assignTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td>
          <td class="paramname"><em>m</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em> = <code>-1</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.assignTo(</td><td class="paramname">m[, type]</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="a538fc6d75281b4ecb7ad50e4555f3fc6"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a538fc6d75281b4ecb7ad50e4555f3fc6">◆ </a></span>channels()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">int cv::cuda::GpuMat::channels </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.channels(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns number of channels </p>
</div>
</div>
<a id="ae1d42819f7f3251478cd6edab8069758"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ae1d42819f7f3251478cd6edab8069758">◆ </a></span>clone()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::clone </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.clone(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns deep copy of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a>, i.e. the data is copied </p>
</div>
</div>
<a id="aac2b18c2ef3fbefc6f776cc313b966c0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aac2b18c2ef3fbefc6f776cc313b966c0">◆ </a></span>col()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::col </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>x</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.col(</td><td class="paramname">x</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns a new <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for the specified column </p>
</div>
</div>
<a id="a7256892911593daf1bdefb183d6fd29e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7256892911593daf1bdefb183d6fd29e">◆ </a></span>colRange() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::colRange </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>startcol</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>endcol</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.colRange(</td><td class="paramname">startcol, endcol</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.colRange(</td><td class="paramname">r</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>... for the specified column span </p>
</div>
</div>
<a id="acfcbd3a61ca20ec908dc6de76ef6e5bb"></a>
<h2 class="memtitle"><span class="permalink"><a href="#acfcbd3a61ca20ec908dc6de76ef6e5bb">◆ </a></span>colRange() <span class="overload">[2/2]</span></h2>
<div class="memitem">
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      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::colRange </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> </td>
          <td class="paramname"><em>r</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.colRange(</td><td class="paramname">startcol, endcol</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.colRange(</td><td class="paramname">r</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="a3a1b076e54d8a8503014e27a5440d98a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3a1b076e54d8a8503014e27a5440d98a">◆ </a></span>convertTo() <span class="overload">[1/5]</span></h2>
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          <td class="memname">void cv::cuda::GpuMat::convertTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rtype</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha[, dst[, beta]]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, beta, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype (Blocking call) </p>
</div>
</div>
<a id="a079d3d6541bb2fe6127c8f5d58953c9c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a079d3d6541bb2fe6127c8f5d58953c9c">◆ </a></span>convertTo() <span class="overload">[2/5]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::convertTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rtype</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha[, dst[, beta]]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, beta, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype (Non-Blocking call) </p>
</div>
</div>
<a id="a656ac1f6a1426527f838c19e2d677dc0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a656ac1f6a1426527f838c19e2d677dc0">◆ </a></span>convertTo() <span class="overload">[3/5]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::convertTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rtype</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double </td>
          <td class="paramname"><em>alpha</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double </td>
          <td class="paramname"><em>beta</em> = <code>0.0</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha[, dst[, beta]]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, beta, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype with scaling (Blocking call) </p>
</div>
</div>
<a id="a54f6bde0a55552bc80a48ecbc8e272d6"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a54f6bde0a55552bc80a48ecbc8e272d6">◆ </a></span>convertTo() <span class="overload">[4/5]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::convertTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rtype</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double </td>
          <td class="paramname"><em>alpha</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha[, dst[, beta]]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, beta, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype with scaling (Non-Blocking call) </p>
</div>
</div>
<a id="a408e9ba5344ab7d3aa27323774de118e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a408e9ba5344ab7d3aa27323774de118e">◆ </a></span>convertTo() <span class="overload">[5/5]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::convertTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rtype</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double </td>
          <td class="paramname"><em>alpha</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">double </td>
          <td class="paramname"><em>beta</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha[, dst[, beta]]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.convertTo(</td><td class="paramname">rtype, alpha, beta, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>converts <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> to another datatype with scaling (Non-Blocking call) </p>
</div>
</div>
<a id="a948c562ee340c0678a44884bde1f5a3e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a948c562ee340c0678a44884bde1f5a3e">◆ </a></span>copyTo() <span class="overload">[1/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::copyTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>copies the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> content to device memory (Blocking call) </p>
</div>
</div>
<a id="adf64af21a2bb13276269584c2a6e1b81"></a>
<h2 class="memtitle"><span class="permalink"><a href="#adf64af21a2bb13276269584c2a6e1b81">◆ </a></span>copyTo() <span class="overload">[2/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::copyTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>copies the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> content to device memory (Non-Blocking call) </p>
</div>
</div>
<a id="ad47f7b0aaf53fa904a6381e7d0192145"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad47f7b0aaf53fa904a6381e7d0192145">◆ </a></span>copyTo() <span class="overload">[3/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::copyTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>mask</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>copies those <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to "m" that are marked with non-zero mask elements (Blocking call) </p>
</div>
</div>
<a id="a49b74a0ef2076543de438fadde55de7b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a49b74a0ef2076543de438fadde55de7b">◆ </a></span>copyTo() <span class="overload">[4/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::copyTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>mask</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">stream[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.copyTo(</td><td class="paramname">mask, stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>copies those <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to "m" that are marked with non-zero mask elements (Non-Blocking call) </p>
</div>
</div>
<a id="af21454929f3efba4c783edbc27042200"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af21454929f3efba4c783edbc27042200">◆ </a></span>create() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::create </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>cols</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.create(</td><td class="paramname">rows, cols, type</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.create(</td><td class="paramname">size, type</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>allocates new <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> data unless the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> already has specified size and type </p>
</div>
</div>
<a id="af88f29d92f6fc2c29cd6ff8960954d4e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af88f29d92f6fc2c29cd6ff8960954d4e">◆ </a></span>create() <span class="overload">[2/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::create </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> </td>
          <td class="paramname"><em>size</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>type</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.create(</td><td class="paramname">rows, cols, type</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.create(</td><td class="paramname">size, type</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="abd47c99304aa165d2214ce9991313bdd"></a>
<h2 class="memtitle"><span class="permalink"><a href="#abd47c99304aa165d2214ce9991313bdd">◆ </a></span>cudaPtr()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void* cv::cuda::GpuMat::cudaPtr </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.cudaPtr(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="ad3e0ed263377f0989c3490f3d496a201"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad3e0ed263377f0989c3490f3d496a201">◆ </a></span>defaultAllocator()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static <a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a>* cv::cuda::GpuMat::defaultAllocator </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda.GpuMat_defaultAllocator(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>default allocator </p>
</div>
</div>
<a id="aaa229d9b2b2f60ecae3b5fbf0603c1b9"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aaa229d9b2b2f60ecae3b5fbf0603c1b9">◆ </a></span>depth()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">int cv::cuda::GpuMat::depth </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.depth(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns element type </p>
</div>
</div>
<a id="a027e74e4364ddfd9687b58aa5db8d4e8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a027e74e4364ddfd9687b58aa5db8d4e8">◆ </a></span>download() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::download </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.download(</td><td class="paramname">[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.download(</td><td class="paramname">stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Performs data download from <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Blocking call) </p>
<p>This function copies data from device memory to host memory. As being a blocking call, it is guaranteed that the copy operation is finished when this function returns. </p>
</div>
</div>
<a id="a2522fd0642c30e0455ec52a28bd3be7b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a2522fd0642c30e0455ec52a28bd3be7b">◆ </a></span>download() <span class="overload">[2/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::download </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#gaad17fda1d0f0d1ee069aebb1df2913c0">OutputArray</a> </td>
          <td class="paramname"><em>dst</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.download(</td><td class="paramname">[, dst]</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>dst</td><td>=</td><td>cv.cuda_GpuMat.download(</td><td class="paramname">stream[, dst]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Performs data download from <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Non-Blocking call) </p>
<p>This function copies data from device memory to host memory. As being a non-blocking call, this function may return even if the copy operation is not finished.</p>
<p>The copy operation may be overlapped with operations in other non-default streams if <code>stream</code> is not the default stream and <code>dst</code> is <a class="el" href="../../d0/d44/classcv_1_1cuda_1_1HostMem.html" title="Class with reference counting wrapping special memory type allocation functions from CUDA...">HostMem</a> allocated with <a class="el" href="../../d0/d44/classcv_1_1cuda_1_1HostMem.html#aa0d69b2aa95680a6b2af6dc4dda44e16a968d788513648797c888aa13e056d6a4">HostMem::PAGE_LOCKED</a> option. </p>
</div>
</div>
<a id="a7e73b4fa94d32e0585564217ebe3fc6c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7e73b4fa94d32e0585564217ebe3fc6c">◆ </a></span>elemSize()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">size_t cv::cuda::GpuMat::elemSize </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.elemSize(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns element size in bytes </p>
</div>
</div>
<a id="a988831407704239eadc036df1b615de5"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a988831407704239eadc036df1b615de5">◆ </a></span>elemSize1()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">size_t cv::cuda::GpuMat::elemSize1 </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.elemSize1(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns the size of element channel in bytes </p>
</div>
</div>
<a id="a509710f61e3a7e13b5ebb2b40984900a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a509710f61e3a7e13b5ebb2b40984900a">◆ </a></span>empty()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">bool cv::cuda::GpuMat::empty </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.empty(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns true if <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> data is NULL </p>
</div>
</div>
<a id="a400fc4c7880bf132f2ffea03892486b0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a400fc4c7880bf132f2ffea03892486b0">◆ </a></span>isContinuous()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">bool cv::cuda::GpuMat::isContinuous </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.isContinuous(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns true iff the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> data is continuous (i.e. when there are no gaps between successive rows) </p>
</div>
</div>
<a id="a934d25560bfb1f03c0077e437d41e0cb"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a934d25560bfb1f03c0077e437d41e0cb">◆ </a></span>locateROI()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::locateROI </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> &amp; </td>
          <td class="paramname"><em>wholeSize</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga1e83eafb2d26b3c93f09e8338bcab192">Point</a> &amp; </td>
          <td class="paramname"><em>ofs</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.locateROI(</td><td class="paramname">wholeSize, ofs</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>locates <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header within a parent <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> </p>
</div>
</div>
<a id="a8b0aa2f9bdf8b40f43be8d8068f2e389"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a8b0aa2f9bdf8b40f43be8d8068f2e389">◆ </a></span>operator PtrStep&lt; _Tp &gt;()</h2>
<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename _Tp &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::operator PtrStep&lt; _Tp &gt; </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
</div><div class="memdoc">
</div>
</div>
<a id="a939f8ef4be2fc9a51058c2404d491f74"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a939f8ef4be2fc9a51058c2404d491f74">◆ </a></span>operator PtrStepSz&lt; _Tp &gt;()</h2>
<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename _Tp &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">cv::cuda::GpuMat::operator PtrStepSz&lt; _Tp &gt; </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
</div><div class="memdoc">
</div>
</div>
<a id="a2b3c25e36b0f82ca8f9f74b6ae68c41d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a2b3c25e36b0f82ca8f9f74b6ae68c41d">◆ </a></span>operator()() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::operator() </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> </td>
          <td class="paramname"><em>rowRange</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> </td>
          <td class="paramname"><em>colRange</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table>
</div><div class="memdoc">
<p>extracts a rectangular sub-GpuMat (this is a generalized form of row, rowRange etc.) </p>
</div>
</div>
<a id="a217e27e7051bed168c34ba767915cc63"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a217e27e7051bed168c34ba767915cc63">◆ </a></span>operator()() <span class="overload">[2/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::operator() </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga11d95de507098e90bad732b9345402e8">Rect</a> </td>
          <td class="paramname"><em>roi</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
</div><div class="memdoc">
</div>
</div>
<a id="ad1432eed28a34f995a641a296281e01c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad1432eed28a34f995a641a296281e01c">◆ </a></span>operator=()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a>&amp; cv::cuda::GpuMat::operator= </td>
          <td>(</td>
          <td class="paramtype">const <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td>
          <td class="paramname"><em>m</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">
<p>assignment operators </p>
</div>
</div>
<a id="aa83fa0825c60eb22a11a87a98c3cd5ed"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa83fa0825c60eb22a11a87a98c3cd5ed">◆ </a></span>ptr() <span class="overload">[1/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a>* cv::cuda::GpuMat::ptr </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>y</em> = <code>0</code></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">
<p>returns pointer to y-th row </p>
</div>
</div>
<a id="ad95918b9342332a41a584b21134b0959"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad95918b9342332a41a584b21134b0959">◆ </a></span>ptr() <span class="overload">[2/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">const <a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a>* cv::cuda::GpuMat::ptr </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>y</em> = <code>0</code></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
</div><div class="memdoc">
</div>
</div>
<a id="af0389962003eec644007c7ca85a04f6d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af0389962003eec644007c7ca85a04f6d">◆ </a></span>ptr() <span class="overload">[3/4]</span></h2>
<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename _Tp &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">_Tp* cv::cuda::GpuMat::ptr </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>y</em> = <code>0</code></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">
<p>template version of the above method </p>
</div>
</div>
<a id="a2d7003ff9fa0a24c5e4986174c29820f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a2d7003ff9fa0a24c5e4986174c29820f">◆ </a></span>ptr() <span class="overload">[4/4]</span></h2>
<div class="memitem">
<div class="memproto">
<div class="memtemplate">
template&lt;typename _Tp &gt; </div>
      <table class="memname">
        <tr>
          <td class="memname">const _Tp* cv::cuda::GpuMat::ptr </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>y</em> = <code>0</code></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
</div><div class="memdoc">
</div>
</div>
<a id="a460951a00945774e9da0b1062ea0a319"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a460951a00945774e9da0b1062ea0a319">◆ </a></span>release()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::release </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">
<p>decreases reference counter, deallocate the data when reference counter reaches 0 </p>
</div>
</div>
<a id="a408e22ed824d1ddf59f58bda895017a8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a408e22ed824d1ddf59f58bda895017a8">◆ </a></span>reshape()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::reshape </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>cn</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>rows</em> = <code>0</code> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.reshape(</td><td class="paramname">cn[, rows]</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>creates alternative <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for the same data, with different number of channels and/or different number of rows </p>
</div>
</div>
<a id="a8d6954870e3c3eacc0ea85cd38bd86b4"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a8d6954870e3c3eacc0ea85cd38bd86b4">◆ </a></span>row()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::row </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>y</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.row(</td><td class="paramname">y</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns a new <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> header for the specified row </p>
</div>
</div>
<a id="a0bf9a88fc518cc9986808aaf916f2182"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a0bf9a88fc518cc9986808aaf916f2182">◆ </a></span>rowRange() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::rowRange </td>
          <td>(</td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>startrow</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">int </td>
          <td class="paramname"><em>endrow</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.rowRange(</td><td class="paramname">startrow, endrow</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.rowRange(</td><td class="paramname">r</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>... for the specified row span </p>
</div>
</div>
<a id="aabccb49164b02284e26884360b7062e8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aabccb49164b02284e26884360b7062e8">◆ </a></span>rowRange() <span class="overload">[2/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> cv::cuda::GpuMat::rowRange </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../da/d35/classcv_1_1Range.html">Range</a> </td>
          <td class="paramname"><em>r</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.rowRange(</td><td class="paramname">startrow, endrow</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.rowRange(</td><td class="paramname">r</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="a5cc463cf6516957a2d78bd03c6d81de5"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a5cc463cf6516957a2d78bd03c6d81de5">◆ </a></span>setDefaultAllocator()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static void cv::cuda::GpuMat::setDefaultAllocator </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">GpuMat::Allocator</a> * </td>
          <td class="paramname"><em>allocator</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda.GpuMat_setDefaultAllocator(</td><td class="paramname">allocator</td><td>)</td></tr></table>
</div><div class="memdoc">
</div>
</div>
<a id="ab263999dea4f7f28d4dd4ced6d2e970b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab263999dea4f7f28d4dd4ced6d2e970b">◆ </a></span>setTo() <span class="overload">[1/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a>&amp; cv::cuda::GpuMat::setTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> </td>
          <td class="paramname"><em>s</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, stream</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask, stream</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s (Blocking call) </p>
</div>
</div>
<a id="aa155961a4c8c19bdb2c9b1886e45ce9a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa155961a4c8c19bdb2c9b1886e45ce9a">◆ </a></span>setTo() <span class="overload">[2/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a>&amp; cv::cuda::GpuMat::setTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> </td>
          <td class="paramname"><em>s</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, stream</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask, stream</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s (Non-Blocking call) </p>
</div>
</div>
<a id="a16cb9be32213df86f3b55ec131abff70"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a16cb9be32213df86f3b55ec131abff70">◆ </a></span>setTo() <span class="overload">[3/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a>&amp; cv::cuda::GpuMat::setTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> </td>
          <td class="paramname"><em>s</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>mask</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, stream</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask, stream</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s, according to the mask (Blocking call) </p>
</div>
</div>
<a id="a1090e7ff25e23cf6243809e9a031b51d"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1090e7ff25e23cf6243809e9a031b51d">◆ </a></span>setTo() <span class="overload">[4/4]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a>&amp; cv::cuda::GpuMat::setTo </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a> </td>
          <td class="paramname"><em>s</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>mask</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, stream</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.setTo(</td><td class="paramname">s, mask, stream</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>sets some of the <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> elements to s, according to the mask (Non-Blocking call) </p>
</div>
</div>
<a id="ab02f97698d8272f0d253f3029329ed10"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab02f97698d8272f0d253f3029329ed10">◆ </a></span>size()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> cv::cuda::GpuMat::size </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.size(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> size : width == number of columns, height == number of rows </p>
</div>
</div>
<a id="a5ead91d096cca20e59ba9af8574187cc"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a5ead91d096cca20e59ba9af8574187cc">◆ </a></span>step1()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">size_t cv::cuda::GpuMat::step1 </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.step1(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns step/elemSize1() </p>
</div>
</div>
<a id="a7135c058aef51c37884a2b2ae8151631"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7135c058aef51c37884a2b2ae8151631">◆ </a></span>swap()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::swap </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html">GpuMat</a> &amp; </td>
          <td class="paramname"><em>mat</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.swap(</td><td class="paramname">mat</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>swaps with other smart pointer </p>
</div>
</div>
<a id="ab0c835e86e2af3c8fc14fee8a2937281"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab0c835e86e2af3c8fc14fee8a2937281">◆ </a></span>type()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">int cv::cuda::GpuMat::type </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>retval</td><td>=</td><td>cv.cuda_GpuMat.type(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>returns element type </p>
</div>
</div>
<a id="a700ad759547d8c4255833e1fa0e6f751"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a700ad759547d8c4255833e1fa0e6f751">◆ </a></span>updateContinuityFlag()</h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::updateContinuityFlag </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.updateContinuityFlag(</td><td class="paramname"></td><td>)</td></tr></table>
</div><div class="memdoc">
<p>internal use method: updates the continuity flag </p>
</div>
</div>
<a id="a00ef5bfe18d14623dcf578a35e40a46b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a00ef5bfe18d14623dcf578a35e40a46b">◆ </a></span>upload() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void cv::cuda::GpuMat::upload </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>arr</em></td><td>)</td>
          <td></td>
        </tr>
      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.upload(</td><td class="paramname">arr</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.upload(</td><td class="paramname">arr, stream</td><td>)</td></tr></table>
</div><div class="memdoc">
<p>Performs data upload to <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Blocking call) </p>
<p>This function copies data from host memory to device memory. As being a blocking call, it is guaranteed that the copy operation is finished when this function returns. </p>
</div>
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<a id="a89d1f885b9f5a479a7c4eb319e7368ae"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a89d1f885b9f5a479a7c4eb319e7368ae">◆ </a></span>upload() <span class="overload">[2/2]</span></h2>
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          <td class="memname">void cv::cuda::GpuMat::upload </td>
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          <td class="paramtype"><a class="el" href="../../dc/d84/group__core__basic.html#ga353a9de602fe76c709e12074a6f362ba">InputArray</a> </td>
          <td class="paramname"><em>arr</em>, </td>
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          <td class="paramkey"></td>
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          <td class="paramtype"><a class="el" href="../../d9/df3/classcv_1_1cuda_1_1Stream.html">Stream</a> &amp; </td>
          <td class="paramname"><em>stream</em> </td>
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          <td>)</td>
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      </table><table class="python_language"><tr><th colspan="999" style="text-align:left">Python:</th></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.upload(</td><td class="paramname">arr</td><td>)</td></tr><tr><td style="width: 20px;"></td><td>None</td><td>=</td><td>cv.cuda_GpuMat.upload(</td><td class="paramname">arr, stream</td><td>)</td></tr></table>
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<p>Performs data upload to <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> (Non-Blocking call) </p>
<p>This function copies data from host memory to device memory. As being a non-blocking call, this function may return even if the copy operation is not finished.</p>
<p>The copy operation may be overlapped with operations in other non-default streams if <code>stream</code> is not the default stream and <code>dst</code> is <a class="el" href="../../d0/d44/classcv_1_1cuda_1_1HostMem.html" title="Class with reference counting wrapping special memory type allocation functions from CUDA...">HostMem</a> allocated with <a class="el" href="../../d0/d44/classcv_1_1cuda_1_1HostMem.html#aa0d69b2aa95680a6b2af6dc4dda44e16a968d788513648797c888aa13e056d6a4">HostMem::PAGE_LOCKED</a> option. </p>
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<h2 class="groupheader">Member Data Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a1dc1f7a23c89d2a36f0efc7db1b0d5a4">◆ </a></span>allocator</h2>
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          <td class="memname"><a class="el" href="../../df/d98/classcv_1_1cuda_1_1GpuMat_1_1Allocator.html">Allocator</a>* cv::cuda::GpuMat::allocator</td>
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<p>allocator </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a9265a32d8d29fe29804a0cb8f57213e9">◆ </a></span>cols</h2>
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          <td class="memname">int cv::cuda::GpuMat::cols</td>
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<h2 class="memtitle"><span class="permalink"><a href="#a5139f9492f9079c7b9e414d50da332a3">◆ </a></span>data</h2>
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          <td class="memname"><a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a>* cv::cuda::GpuMat::data</td>
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<p>pointer to the data </p>
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<a id="ad76c4f58490134f1acf3e580e669c58b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad76c4f58490134f1acf3e580e669c58b">◆ </a></span>dataend</h2>
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          <td class="memname">const <a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a>* cv::cuda::GpuMat::dataend</td>
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<h2 class="memtitle"><span class="permalink"><a href="#ade4a4dfc61facd5f18143b4c9d56dbae">◆ </a></span>datastart</h2>
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          <td class="memname"><a class="el" href="../../d1/d1b/group__core__hal__interface.html#ga65f85814a8290f9797005d3b28e7e5fc">uchar</a>* cv::cuda::GpuMat::datastart</td>
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<p>helper fields used in locateROI and adjustROI </p>
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<h2 class="memtitle"><span class="permalink"><a href="#adfd242b365e79ebc382a0829d8e9f44f">◆ </a></span>flags</h2>
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<p>includes several bit-fields:</p><ul>
<li>the magic signature</li>
<li>continuity flag</li>
<li>depth</li>
<li>number of channels </li>
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<h2 class="memtitle"><span class="permalink"><a href="#af528e8b675a72fd79ff1f399b7dd42df">◆ </a></span>refcount</h2>
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          <td class="memname">int* cv::cuda::GpuMat::refcount</td>
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<p>pointer to the reference counter; when <a class="el" href="../../d0/d60/classcv_1_1cuda_1_1GpuMat.html" title="Base storage class for GPU memory with reference counting. ">GpuMat</a> points to user-allocated data, the pointer is NULL </p>
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<h2 class="memtitle"><span class="permalink"><a href="#a7385022ca9114e5f5058dbb2f12467cb">◆ </a></span>rows</h2>
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          <td class="memname">int cv::cuda::GpuMat::rows</td>
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<p>the number of rows and columns </p>
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<h2 class="memtitle"><span class="permalink"><a href="#af46427ea4c9b3fe7687e3afa84baede3">◆ </a></span>step</h2>
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<p>a distance between successive rows in bytes; includes the gap if any </p>
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<hr/>The documentation for this class was generated from the following file:<ul>
<li>opencv2/core/<a class="el" href="../../d8/dd1/modules_2core_2include_2opencv2_2core_2cuda_8hpp.html">cuda.hpp</a></li>
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